Inferring Point Cloud Quality via Graph Similarity

05/31/2020
by   Qi Yang, et al.
0

We propose the GraphSIM – an objective metric to accurately predict the subjective quality of point cloud with superimposed geometry and color impairments. Motivated by the facts that human vision system is more sensitive to the high spatial-frequency components (e.g., contours, edges), and weighs more to the local structural variations rather individual point intensity, we first extract geometric keypoints by resampling the reference point cloud geometry information to form the object skeleton; we then construct local graphs centered at these keypoints for both reference and distorted point clouds, followed by collectively aggregating color gradient moments (e.g., zeroth, first, and second) that are derived between all other points and centered keypoint in the same local graph for significant feature similarity (a.k.a., local significance) measurement; Final similarity index is obtained by pooling the local graph significance across all color channels and by averaging across all graphs. Our GraphSIM is validated using two large and independent point cloud assessment datasets that involve a wide range of impairments (e.g., re-sampling, compression, additive noise), reliably demonstrating the state-of-the-art performance for all distortions with noticeable gains in predicting the subjective mean opinion score (MOS), compared with those point-wise distance-based metrics adopted in standardization reference software. Ablation studies have further shown that GraphSIM is generalized to various scenarios with consistent performance by examining its key modules and parameters.

READ FULL TEXT

page 2

page 4

page 5

page 8

page 9

page 10

page 11

page 12

research
10/10/2022

Evaluating Point Cloud Quality via Transformational Complexity

Full-reference point cloud quality assessment (FR-PCQA) aims to infer th...
research
03/30/2020

A generalized Hausdorff distance based quality metric for point cloud geometry

Reliable quality assessment of decoded point cloud geometry is essential...
research
08/05/2021

Joint Geometry and Color Projection-based Point Cloud Quality Metric

Point cloud coding solutions have been recently standardized to address ...
research
11/25/2020

Reduced Reference Perceptual Quality Model and Application to Rate Control for 3D Point Cloud Compression

In rate-distortion optimization, the encoder settings are determined by ...
research
03/24/2023

GQE-Net: A Graph-based Quality Enhancement Network for Point Cloud Color Attribute

In recent years, point clouds have become increasingly popular for repre...
research
11/24/2021

PointPCA: Point Cloud Objective Quality Assessment Using PCA-Based Descriptors

With the increasing popularity of extended reality technology and the ad...
research
04/10/2023

Evaluate Geometry of Radiance Field with Low-frequency Color Prior

Radiance field is an effective representation of 3D scenes, which has be...

Please sign up or login with your details

Forgot password? Click here to reset